Post-stroke depression update 2025: Mechanisms, prediction, and management

Post-stroke depression (PSD) has a stable prevalence of 30%. Beyond stroke severity, lesion location and prior depression, vitamin D deficiency, hyperhomocysteinaemia and insulin resistance are now recognised as independent risk factors. Mechanistically, phenotypic switching of microglia and astrocytes drives neuro-inflammation via NF-κB, JAK-STAT3 and NLRP3 inflammasome signalling. Gut-brain axis studies show reduced Faecalibacterium, increased Enterococcus and decreased short-chain fatty acids. Multi-omics evidence also indicates down-regulation of BDNF/TrkB, glutamate excitotoxicity, hypothalamic-pituitary-adrenal-axis dysregulation and altered miR-146a/34a expression. Predictively, machine-learning models integrating magnetic resonance imaging lesion-network patterns, clinical variables and inflammatory markers achieve area under the curve > 0.90, although external validation is still required. Therapeutically, selective serotonin reuptake inhibitors (sertraline, escitalopram) remain first-line, and evidence for agomelatine, vitamin D and tumor necrosis factor-α inhibitors is increasing. Traditional Chinese medicine (TCM) formulations such as Chaihu Shugan San, Danzhi Xiaoyao San and Shugan Jieyu capsule attenuate neuro-inflammation and restore synaptic plasticity by modulating JAK-STAT3-GSK3β/ PTEN/Akt, Nrf2/HO-1 and NMDAR/BDNF pathways. Additionally, acupuncture, repetitive transcranial magnetic stimulation, exercise and music therapy have proven safe and effective. Looking ahead, PSD research should integrate multi-omics, artificial intelligence and individualised TCM to establish a full-chain paradigm for risk prediction and precision stratification.